Szczegóły publikacji
Opis bibliograficzny
A new approach to border irregularity assessment with application in skin pathology / Paweł KŁECZEK, Grzegorz Dyduch, Agnieszka Graczyk-Jarzynka, Joanna JAWOREK-KORJAKOWSKA // Applied Sciences (Basel) [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2076-3417. — 2019 — vol. 9 iss. 10 art. no. 2022, s. 1–24. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 22–24, Abstr. — Publikacja dostępna online od: 2019-05-16
Autorzy (4)
- AGHKłeczek Paweł
- Dyduch Grzegorz
- Graczyk-Jarzynka Agnieszka
- AGHJaworek-Korjakowska Joanna
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 122209 |
|---|---|
| Data dodania do BaDAP | 2019-07-01 |
| Tekst źródłowy | URL |
| DOI | 10.3390/app9102022 |
| Rok publikacji | 2019 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Applied Sciences (Basel) |
Abstract
The border irregularity assessment of tissue structures is an important step in medical diagnostics (e.g., in dermatoscopy, pathology, and cardiology). The diagnostic criteria based on the degree of uniformity and symmetry of border irregularities are particularly vital in dermatopathology, to distinguish between benign and malignant skin lesions. We propose a new method for the segmentation of individual border projections and measuring their morphometry. It is based mainly on analyzing the curvature of the object’s border to identify endpoints of projection bases, and on analyzing object’s skeleton in the graph representation to identify bases of projections and their location along the object’s main axis. The proposed segmentation method has been tested on 25 skin whole slide images of common melanocytic lesions. In total, 825 out of 992 (83%) manually segmented retes (projections of epidermis) were detected correctly and the Jaccard similarity coefficient for the task of detecting retes was 0.798. Experimental results verified the effectiveness of the proposed approach. Our method is particularly well suited for assessing the border irregularity of human epidermis and thus could help develop computer-aided diagnostic algorithms for skin cancer detection.
